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Record W4417004679 · doi:10.1182/blood-2025-4608

CPX-351 is a feasible bridge to allogeneic hematopoietic stem cell transplantation in TP53 mutated acute myeloid leukemia with  myelodisplastic related changes or therapy related without del(17p): Sub-analysis from a large italian real world retrospective study

2025· article· en· W4417004679 on OpenAlexaff
Elisabetta Todisco, Ivana Lotesoriere, Federico Lussana, Valentina Mancini, Federica Gigli, Cristina Papayannidis, Michela Rondoni, Felicetto Ferrara, Sara Mastaglio, Annalina Piccioni, Michelina Dargenio, Andrea Corbingi, Francesco Mannelli, Alessandro Cignetti, Patrizia Zappasodi, Maria Paola Martelli, Monia Lunghi, Luana Fianchi, Patrizia Chiusolo, Francesco Grimaldi, Federica Pilo, Carla Filì, Debora Capelli, M. Breccia, Monica Bocchia, Monica Fumagalli, Sara Galimberti, Luca Maurillo, Calogero Vetro, Alessandra Sperotto, Caterina Patti, Erika Borlenghi, Federica Lessi, Alessandro Isidori, Raffaele Palmieri, Caterina Alati, Samuele Gatani, Chiara Pessina, Paola Minetto, Carola Riva, Marco Frigeni, Nicola Stefano Fracchiolla, Carla Mazzone, Marco Cerrano, Massimo Bernardi, Michele Gottardi, Roberto Cairoli, Adriano Venditti, Livio Pagano, Roberto M. Lemoli, Fabio Guolo

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMyeloid leukemiaContext (archaeology)HematologyHematopoietic stem cell transplantationTransplantationLeukemiaPopulationMyeloid

Abstract

fetched live from OpenAlex

Abstract CPX-351 has been approved for Acute Myeloid Leukemia (AML) with myelodysplasia related changes (AML-MRC) and therapy-related (t-AML) induction. The likelihood of TP53 mutations (TP53m) in this setting is 20-35% but, considering the many variables of TP53m topography and configuration, the assessment of the prognostic impact of TP53 lesions may be challenging. This is the largest subanalysis about the outcome of TP53m AML-MRC and t-AML patients (pts) homogeneously treated with CPX-351 and has been conducted between January 2019 and December 2021 within the italian retrospective real world study about 513 pts (Guolo F. and Todisco E., paper submitted to American Journal of Hematology). Over 335 evaluable pts, in 51 (15%), 39 AML-MRC and 12 t-AML, TP53m were detected by Sanger (n=5) or Next Generation Sequencing (n=28) analysis or both (n=18). Median age was 63 years (range 23-73). Among the 286 TP53 wild-type pts (TP53w), 162 (57%) had complex karyotype (CK) and 10 (3%) del(17p) (9 of which in the context of CK) while, among the 51 TP53m pts, CK was found in 29 (57%) and del(17p) in 6 (12%) (5 of which with CK). According to Grob T. et al., Blood 2022, 26 of 50 evaluable TP53m pts (51%) were classified as biallelic. We also analysed the TP53m population according to Bahaj W. et al., Journal of Hematology & Oncology 2023 (applicable in 40 pts) finding substantial overlap in the assignment of allelic status. According to both classifications, a CK was significantly more frequent among biallelic mutated pts: 22 CK/26 biallelic mutated pts (85%), vs 6/24 (25%) among monoallelic (p<0.05) while all pts with a del(17p) had a biallelic mutation. Twenty-four of 51 TP53m pts (47%) and 162 of 286 TP53wt pts (57%) obtained complete remission or complete remission with incomplete hematologic recovery (CR/CRi) (p .096). In multivariate analysis for CR considering molecular and cytogenetic characteristics including allelic TP53 status, del(17p) resulted the only variable with independent negative prognostic impact (p .018, HR 1.05-1.55). In fact, among the 6 pts with del(17p), none achieved CR. Overall, 122/286 (43%) TP53wt pts and 15/51 (29%) of the TP53m cohort underwent allogeneic stem cell transplantation (allo-SCT). Among the 15 TP53m transplanted pts, 40% (n=6) had a biallelic mutation, 33% (n=5) had CK (but none with del(17p). After a median follow up of 23,67 months (m) (CI 95% 21.47-25.86), median OS (mOS) of the TP53w population was 17,1 m (range 16.7-20.27) vs 9,5 m (range 6.8-12.4) for TP53m, p .064; no significative difference but a trend was observed between TP53w and TP53 mono vs biallelic (mOS 17.1 m and 18.53 m vs 8.2 m respectively, p .110). We have therefore performed analyses based on the presence of CK: mOS was 19,3 m for TP53w pts without CK and 14,6 m for those carrying CK (p .117) vs respectively 32,5 m and 11,5 m (p .053) within TP53m cohort. A CK was not significantly related to a worse survival regardless of allelic status (mOS not reached and 10.3 m for pts without CK with mono and biallelic mutation vs respectively 4.7 m and 7.9 m for those with CK, p .496). Within the TP53m cohort, the presence of a missense TP53m vs other mutations (frameshift, nonsense, splice or intronic) resulted in non significant survival difference (p .213) as between canonical or non canonical missense TP53m (p .265). Furthermore, we did not find any impact on survival when we considered co-mutations (available only in 35 of 51 TP53m pts), their number or combinations. Del(17p) was instead the only factor having a negative impact on survival (mOS 4,7 m with del(17p) vs 13,6 m without, p.005). In a landmark analysis of TP53m pts alive and in 1st CR at 3 m who underwent allo-SCT (n=15, 62% of those achieving CR), mOS was not reached vs 10,3 m for not transplanted pts (p .347). We were unable to perform further subanalyses in this context because of the small population size. Although the incidence of TP53 mutations is likely underestimated due to the retrospective nature of the study, our analysis shows that CPX-351 is a feasible therapeutic option as bridge to allo-SCT also in a difficult subset like TP53m AML-MRC and t-AML unless if del(17p) is also present. We are conducting a retrospective and prospective expansion of the study in order to verify our findings on a larger sample size.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.291
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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